Supermarket Refrigeration Research Articles

ENERGY AND ENVIRONMENTAL ANALYSIS OF TRANSCRITICAL CO2 SUPERMARKET REFRIGERATION CYCLES WITH DEDICATED MECHANICAL SUBCOOLER

Refrigerants with high environmental impact are being prohibited by legal authorities. The commercial refrigeration sector, a huge contributor to emissions, is transitioning to environmentally friendly CO2 systems. Despite the environmental benefits of CO2, its low critical temperature and high operation pressure can lead to lower performance in warm climates compared to other refrigerants. Therefore, performance improvements are being made for transcritical CO2 refrigeration cycles. This paper presents energy and environmental analysis of transcritical booster (BRC), parallel compression (PRC), and ejector expansion (ERC) supermarket refrigeration cycles with dedicated mechanical subcooler (DMS) as well as transcritical cycles without DMS circuits, and subcritical R404A conventional system. R134a, R1234yf, and R290 were studied as working fluids for DMS circuits. Annual energy consumption and total equivalent warming impact (TEWI) values were compared for İstanbul, Konya, and Samsun in Türkiye, which are in different climate zones, as a case study. The case study constitutes the novelty of this paper. Up to 11% annual energy savings were obtained using CO2 cycles with DMS compared to R404A conventional system. CO2 cycles have up to 58.4% lower total TEWI values than R404A conventional system

Thermal energy export from supermarket refrigeration systems: Drivers and barriers

Supermarket refrigeration systems offer the possibility to recover significant amounts of energy. These amounts may at times be higher than what the supermarket needs. In these cases, export of heat or air conditioning to neighboring buildings is a solution for increased overall energy efficiency. However, although previous studies have demonstrated the technical viability of such systems, they are rarely implemented in practice. In this work, possible barriers to and drivers of implementation of thermal energy export from supermarkets are investigated. The empirical work consists of a mixed-method data collection and in-depth analysis of six case studies of supermarkets that are in a research collaboration project between the KTH Royal Institute of Technology in Stockholm and CIT Energy Management in Gothenburg, Sweden. The main findings indicate that several barriers, especially the split economic incentives of supermarkets and property owners and a lack of information, have significant detrimental effects on the uptake of thermal energy export solutions. Cooperative agreements between supermarkets and property owners are found to have the greatest possibility to mitigate the impact of the barriers, but standardized templates are needed to reduce their associated legal, technical, and administrative uncertainties.

Comparative thermodynamic study of CO2 transcritical supermarket booster refrigeration system combined with vapor injection and parallel compressionÉtude thermodynamique Comparative du système de réfrigération transcritique de supermarché au CO2 combiné à l'injection de vapeur et à la compression parallèle

The use of CO2 refrigerants in supermarket refrigeration has recently demonstrated great potential owing to their excellent thermophysical properties and environmental protection. To further improve the efficiency of transcritical CO2 refrigeration systems, a parallel compression cycle with vapor injection system (SRC) is proposed. Thermodynamic model is established to investigate the influence of working condition parameters and compared with basic booster refrigeration system (BRC) and parallel compression refrigeration system (PRC). In addition, the effect of vapor injection parameters on the characteristics of the proposed system is investigated. The results show that the medium pressure has little effect on BRC, while the optimum value exists for both PRC and SRC. The performance of the three systems can be significantly enhanced by optimizing the discharge pressure and medium pressure. The optimal value of the relative vapor injection pressure is constant at about 1.15. The maximum coefficient of performance (COPmax) of the SRC is significantly improved by 23.99%∼32.14% and 14.44%∼20.07% at disccussed working conditions compared with BRC and PRC, respectively. In summary, this paper confirms the performance enhancement potential of the proposed cycle and provides theoretical support for its practical implementation.

Waste heat utilization: Energy and economic benefits from multi-ejector chiller sub-cooling R744 supermarket refrigeration systems

This study investigated the energy and economic benefits of a novel sub-cooling technique using a heat-driven multi-ejector chiller (HDEC) in R744 supermarket refrigeration systems. Two configurations were evaluated: a conventional booster system with HDEC (CBEC) and a parallel compression system with HDEC (PCEC). Among various natural refrigerants, R717 was identified as most suitable for the HDEC. Various multi-ejector combinations were examined to assess the potential for waste heat utilization and energy savings in the R744 refrigeration system. The CBEC system provided effective operation only at ambient temperatures above 31 °C, whereas the PCEC system was effective above 24 °C. Performance of the proposed configurations were compared with a conventional R744 booster system (CB) and a parallel compression system (PC) both devoid of HDEC. The PCEC system showed improvements in the coefficient-of-performance ranging from 4.2 % to 23.9 % at ambient temperatures between 28 °C and 40 °C compared to the baselines. In various warm-climatic zones, including India, the Middle East, Thailand, and the USA, energy savings of approximately 2.1 %–9.5 % were observed compared to the PC system. Economic analysis indicated a reasonable payback period of 2.1–2.7 years for the additional investment required for deploying the PCEC system in Phoenix.

High-fidelity model development of CO2 booster refrigeration systems in supermarkets using field measurements

Supermarket refrigeration systems adopting traditional refrigerants with high global warming potential (GWP) have impacts on global warming for indirect and direct greenhouse gases (GHG) emissions. CO2 is a popular low-GWP alternative. The transcritical operation of CO2 systems worsens their energy performance, but provides recoverable heat as a heat source to reduce gas consumption. To evaluate operation performance, data-driven models, trained by historical data, are weak in implementation with datasets outside the scope of training data; in contrast, theoretical models have better extrapolation ability to calculate all operation conditions of CO2 systems at supermarket. Existing theoretical modeling approaches often lack validation against the limited public-access data, which reduces model reliability for further applications, and adopt oversimplified inference methods for unmeasured variables, which increases the risks of breaking thermodynamic laws and lowering model accuracy. This study therefore develops a steady-state theoretical model for CO2 booster refrigeration systems validated against field measurements from three UK supermarkets. The available measurements are utilized to the best level to ensure model accuracy and physical interpretability. Proposed methods to infer missing variables in CO2 systems include condenser outlet temperature, evaporating temperature, compressor isentropic efficiency and compressor mass flow rate. Results show that proposed inference methods enhance the abilities of the proposed modeling approach to ensure data integrity, avoid breaking thermodynamic laws, and improve model accuracy by reflecting real-time actual values of unmeasured variables rather than rough assumptions. The proposed modeling approach provides satisfactory accuracy validated using high-resolution measurements across the whole year from three real supermarkets.

Data-driven modeling of the refrigeration load in supermarkets — A case study on three European supermarkets

When investigating supermarket refrigeration systems, it is essential to consider the refrigeration load as it directly affects the required compressor capacity and energy consumption. Therefore, it is important to have knowledge of the refrigeration load and its main influencing factors.Direct usage of data for the refrigeration load in a whole-year energy simulation can present significant challenges. This is partly due to long lead times for data collection and the challenges posed by missing data. As a result, often there is no complete data set of the refrigeration load for the whole-year. Therefore, a mathematical model can serve as a tool to interpolate and extrapolate the refrigeration load over the course of a year. The model is not intended for transfer to other locations.This paper begins with a overview of correlations found in the literature, followed by the development of an improved model that accounts for the impact of ambient temperature and time on the refrigeration load. Additionally, a novel approach using a neural network is proposed as a second model. Both models are then applied to data from three supermarkets in Europe and the model performance is evaluated.Both models performed acceptably in representing the refrigeration load of all three supermarkets. Especially including the influence of time of day into the first model significantly improves the prediction accuracy. The neural network has the highest prediction performance and can improve the prediction performance by 40% over the improved literature model.

Transcritical CO2 system with two-stage throttling for supermarkets: Field tests, energy and emission performance assessment in China

Transcritical CO2 system is eco-friendly for the application of refrigeration and cooling in supermarket. To evaluate the applicability of transcritical CO2 supermarket refrigeration system in China with different climate regions, this study focuses on the field tests of a transcritical CO2 two-stage throttling system in a supermarket in Suzhou, Jiangsu Province, China. Furthermore, based on the tested data, the system energy and emissions performance models of four system configurations are also developed and validated, including the system integrated with an internal heat exchanger, a parallel compression, and mechanically assisted subcooling. In order to improve the usability of the system in different climatic zones, 40 cities were selected for calculation in China. Five representative cities (Beijing, Harbin, Xiamen, Chongqing, and Kunming) located in different climate regions of China are selected, and the annual performance factor and life cycle climate performance (LCCP) are determined to evaluate the application potential of the CO2 refrigeration systems in different climate conditions. The tested results show the operation mode of transcritical and subcritical changes occurs at an ambient temperature of about 27 °C, at which the coefficient of performance (COP), compressor discharge pressure and discharge temperature change dramatically. The simulation results demonstrate that the mechanical subcooling system shows the best performance. The annual performance factor can be improved by 18.69 % when the mechanical subcooling is adopted. For the case of the system used in Xiamen by using mechanical subcooling, the carbon emissions can be reduced by 19.3 %.

Thermodynamic, environmental, and exergoeconomic analysis of multi-ejector expansion transcritical CO2 supermarket refrigeration cycles in different climate regions of Türkiye

Restrictions on high-GWP refrigerants have made the use of transcritical CO2 refrigeration systems widespread. Using transcritical booster refrigeration cycle in warm climates is unsatisfactory due to its high energy consumption. This paper presents theoretical analysis and performance comparison of three different transcritical CO2 supermarket refrigeration cycle configurations with ejector expansion in Türkiye, which has different climatic regions. Bin-hour data were derived using hourly dry-bulb temperature values for provinces from 7 different regions in Türkiye. The applicability of multi-ejectors to each modeled cycle was also investigated. Annual energy consumption and environmental impact reductions of up to 17% were obtained using ejector expansion cycle compared to booster cycle. Ejector expansion cycles achieved higher performance than booster cycle up to 46% in terms of exergy efficiency at investigated ambient temperatures. Unit product exergy costs of the ejector cycles were found up to 28% lower than booster cycle.

Assessment of booster refrigeration system with eco-friendly working fluid CO2/halogenated alkene (HA) mixture for supermarket application around the world: Energy conservation, cost saving, and emissions reduction potential

For the scope of commercial supermarkets, the demand for energy efficiency improvement and environmentally-friendly working fluid of the refrigeration system is necessary. In this study, supermarket booster refrigeration system by using eco-friendly working fluid CO2/halogenated alkene (HA) mixture is proposed, and the mixture used in systems with two evaporation temperatures and operating modes affected by ambient temperature are studied. The energy efficiency, economic performance and emission reduction potential of the whole life cycle are conducted to compare with the pure CO2 booster refrigeration system. Furthermore, the influence of climate condition is discussed when used in 40 typical cities around the world. The results show the coefficient of performance (COP) of booster refrigeration system can be significantly improved by using CO2/HA mixtures. As the ambient temperature is 33 °C, the CO2/R1234yf (93/7) operates with the maximum COP of 1.367, which is 11.59 % higher than that of pure CO2. Using CO2/HA mixtures in the booster refrigeration system can significantly improve the exergy efficiency of system. Moreover, the system using CO2/HA mixtures has higher annual performance factor and lower life cycle cost (LCC) than pure CO2. LCC of the system using CO2/R1234yf (94/6) is the lowest, and the reduction rate is 3.06–5.59 %. Meanwhile, the life cycle carbon emissions of systems in different climatic regions using CO2/R1234yf can be reduced by 2.39–5.21 %. The booster refrigeration system adopting CO2/HA mixtures is a promising alternative solution for commercial supermarket refrigeration and energy-saving.

Precision Leak Detection in Supermarket Refrigeration Systems Integrating Categorical Gradient Boosting with Advanced Thresholding

Supermarket refrigeration systems are integral to food security and the global economy. Their massive scale, characterized by numerous evaporators, remote condensers, miles of intricate piping, and high working pressure, frequently leads to problematic leaks. Such leaks can have severe consequences, impacting not only the profits of the supermarkets, but also the environment. With the advent of Industry 4.0 and machine learning techniques, data-driven automatic fault detection and diagnosis methods are becoming increasingly popular in managing supermarket refrigeration systems. This paper presents a novel leak-detection framework, explicitly designed for supermarket refrigeration systems. This framework is capable of identifying both slow and catastrophic leaks, each exhibiting unique behaviours. A noteworthy feature of the proposed solution is its independence from the refrigerant level in the receiver, which is a common dependency in many existing solutions for leak detection. Instead, it focuses on parameters that are universally present in supermarket refrigeration systems. The approach utilizes the categorical gradient boosting regression model and a thresholding algorithm, focusing on features that are sensitive to leaks as target features. These include the coefficient of performance, subcooling temperature, superheat temperature, mass flow rate, compression ratio, and energy consumption. In the case of slow leaks, only the coefficient of performance shows a response. However, for catastrophic leaks, all parameters except energy consumption demonstrate responses. This method detects slow leaks with an average F1 score of 0.92 within five days of occurrence. The catastrophic leak detection yields F1 scores of 0.7200 for the coefficient of performance, 1.0000 for the subcooling temperature, 0.4118 for the superheat temperature, 0.6957 for the mass flow rate, and 0.8824 for the compression ratio, respectively.

ENERGY, ENVIRONMENTAL, AND EXERGOECONOMIC (3E) ANALYSIS OF TRANSCRITICAL CO2 BOOSTER AND PARALLEL COMPRESSION SUPERMARKET REFRIGERATION CYCLES IN CLIMATE ZONES OF TÜRKİYE

Legal restrictions on high-GWP refrigerants lead to the widespread use of carbon dioxide in commercial refrigeration, where there is a high energy consumption. Although CO2 has many benefits, its lower critical temperature and higher operation pressure compared to other refrigerants lead to performance reduction. For this reason, studies have been conducted by researchers for performance enhancement. This paper presents energy, environmental impact, and exergoeconomic (3E) analysis of transcritical CO2 booster and parallel compression supermarket refrigeration cycles based on meteorological data of 11 provinces in Türkiye as samples of different climatic regions. Parallel compression cycle achieved up to 18.4% higher coefficient of performance than booster cycle between the investigated ambient temperatures. Up to 5.6% annual energy consumption and environmental impact reduction were obtained using parallel compression. Unit product costs of the parallel compression cycles were calculated between 8.2% and 18% lower than booster cycle in investigated provinces. Developing energy-efficient systems that use environmentally friendly refrigerants will contribute to a sustainable future.

An Evaluation of R448A as R404A low GWP Alternative in a Supermarket Refrigeration Application

An Evaluation of R448A as R404A low GWP Alternative in a Supermarket Refrigeration Application

Performance Analysis of an R744 Supermarket Refrigeration System Integrated with an Organic Rankine Cycle

The energy and economic performance of a transcritical R744 booster supermarket refrigeration system with and without parallel compression and integrated with an organic Rankine cycle (ORC) was investigated. The results obtained were compared with those of a transcritical R744 booster supermarket refrigeration system with and without parallel compression and those of a conventional R404A direct expansion (DX) system. Nine different locations, namely Copenhagen (Denmark), Paris (France), Athens (Greece), New Delhi (India), Phoenix and Miami (US), Madrid (Spain), Bangkok (Thailand) and Riyadh (Saudi Arabia), were considered. It was discovered that the ORC is effective only at ambient temperatures higher than 27 °C when operating without parallel compression and 28 °C when operating with parallel compression. By using the heat recovered from the gas cooler to fuel the ORC, the latter was found to be capable of covering between 4% and 24% of the electricity demand of the R744 system in warm and hot climates (without parallel compression). The simple payback period of the additional investment associated with the ORC was found to be between 1.4 and 2.5 years in warm climate locations, while the same was found to be less than about 0.5 years in locations experiencing hot climatic conditions.

A fault-tolerant control strategy to estimate and compensate the temperature sensor bias in supermarket refrigeration systems

The paper proposes a data-driven fault-tolerant control (FTC) strategy to construct and accommodate the bias on ambient temperature measurements in supermarket refrigeration systems. The bias, which is caused by direct or indirect exposure of the sensor to the sun, can have a significant impact on the refrigeration system’s energy consumption. Based on analysis of the real data a comprehensive model of the bias is developed and then used to generate realistic scenarios for testing the proposed FTC method. The FTC method uses a feed forward Neural Network (NN) as a black box model. The model is trained by active injection of perturbation signals during the night operations. During the Monte-Carlo tests, the strategy was implemented in a Plug & Play manner, demonstrating that substantial energy savings can be achieved during summer periods.

Influence of subcooling in R-449A supermarket refrigeration system and screening of refrigerant mixtures for its energetic and environmental improvement

Current demands of the cooling sector are focused on using refrigerants with a low Global Warming Potential (GWP) and increasing energy efficiency in vapour compression installations. The main objectives of this paperwork arise from these needs, in which the use of subcooling in an R-449A commercial refrigeration system is evaluated. In addition, eco-friendly alternative refrigerants are proposed and studied. Firstly, the effect of an integrated type of subcooling is semi-empirically analysed with Engineering Equation Solver (EES). Then, the refrigeration system’s operation is simulated using low-GWP alternative refrigerants, R-454C and R-290, which have been scarcely studied in commercial refrigeration systems due to their safety classification. Moreover, new refrigerant mixtures are searched from the binary and ternary combination of pure refrigerants using the software REFPROP. The best refrigerant with safety classification A1, A2L, and A2/A3, for both medium temperature (MT) and low temperature (LT) systems is obtained from this search. After their determination, the supermarket’s operation is simulated with these refrigerants. Finally, an environmental assessment is performed. The highest energy efficiency is obtained with R-152a for the MT system and the R-290/R-1270 mixture for the LT system. However, the highest reduction of GHG emissions is achieved by R-290, with a reduction of 73.78 % with respect to the baseline system.

Dynamic model-based feature extraction for fault detection and diagnosis of a supermarket refrigeration system†

With the increasing concerns over climate change and carbon emissions, fault detection and diagnostics (FDD) of low–global warming potential (GWP) refrigerant supermarket refrigeration systems has gained great attention from academic and industrial sectors. Various FDD approaches have been developed to detect, identify, and diagnose faults to save energy, improve food quality, and protect the environment. To mitigate the difficulty of collecting high-quality steady-state operational data in field operations faced by most model-based FDD methods, this study developed dynamic models of a low–GWP refrigerant (CO2) supermarket refrigeration system. The model accuracy was validated using manufacturer data and experimental data. Simulations were conducted to predict the system dynamic response under two common operational faults—evaporator air path blockage fault and the display case door open fault—to identify fault patterns and define key dynamic behavior indexes for supporting FDD algorithm development.

CFD supported thermodynamic analysis of a CO2 pressure exchanger based refrigeration system for supermarkets

This manuscript presents a method to thermodynamically model a pressure exchanger device. CFD-based model of a rotary energy recovery device used in desalination process is developed and validated with published experimental data with a maximum deviation of 5.19%. The dimensionality of the validated model was reduced to investigate the potential of the pressure exchanger device operating with CO2 as the working fluid. Based on the data obtained from several numerical experiments, two correlations were developed, by means of non-linear regression analysis, for estimating the pressure lift generated by the device as a function of inlet velocity of high pressure fluid (0.5 – 3 m/s), rotor speed (500 – 3000 rpm), receiver pressure (25 – 40 bar) and gas-cooler pressure (90 – 120 bar). The correlations were found to be within acceptable error margin. The pressure lift generated by the pressure exchanger was found to be directly proportional to the inlet velocity of the high pressure fluid and inverse proportionality to the rotor speed. The developed correlations are used to evaluate the thermodynamic performance of a multi evaporator supermarket refrigeration system integrated with pressure exchanger to a conventional parallel compression system and a published multi-ejector system in the ambient temperature range of 30 to 40 °C. The pressure exchanger based system was found to outperform the parallel compression as well as the multi-ejector system and demonstrate significant energy savings.

Estimation of evaporator valve sizes in supermarket refrigeration cabinets

In many applications, e.g. fault diagnostics and optimized control of supermarket refrigeration systems, it is important to determine the heat demand of the cabinets. This can easily be achieved by measuring the mass flow through each cabinet, however that is expensive and not feasible in large-scale deployments. Therefore it is important to be able to estimate the valve sizes from the monitoring data, which is typically measured. The valve size is measured by an area, which can be used to calculate mass flow through the valve — this estimated value is referred to as the valve constant. A novel method for estimating the cabinet evaporator valve constants is proposed in the present paper. It is demonstrated using monitoring data from a refrigeration system in a supermarket in Otterup (Denmark), consisting of data sampled at a one-minute sampling rate, however it is shown that a sampling time of around 10–20 min is adequate for the method. Through thermodynamic analysis of a two stage CO2 refrigeration system, a linear regression model for estimating valve constants is developed using time series data. The linear regression requires that transient dynamics are not present in the data, which depends on multiple factors e.g. the sampling time. If dynamics are not modelled it can be detected by a significant auto-correlation of the residuals. In order to include the dynamics in the model, an Auto-Regressive Moving Average model with eXogenous variables (ARMAX) is applied, and it is shown how it effectively eliminates the auto-correlation and provides less bias and higher accuracy of the estimates. Furthermore, it is shown that the sample time has a huge impact on the estimates. Thus, a method for selecting the optimal sampling time is introduced. It works individually for each of the evaporators, by exploring their respective frequency spectrum. That way, a reliable estimate of the actual valve constant can be achieved for each evaporator in the system and it is shown that sampling times above 10 min are optimal for the analysed systems.

Choosing an optimized refrigeration system based on sustainability and operational scenarios applied to four supermarket architectures in three European countries

The growing global demand for refrigeration requires the design of more sustainable systems. However, despite environmentally promising technologies in refrigeration, there are still barriers to their widespread adoption. In this paper, a generic approach able to describe the multiple performances (energy, environmental, economic, social) of refrigeration systems is proposed to assess their potential of adoption. To propose a realistic study framework, four architectures of supermarket refrigeration systems are modelled and simulated using ground data with different climatic conditions and electricity mixes (France, Sweden, Spain). The overall results of these operational scenarios show that the electricity mix is the most influential parameter on cost and environmental impact. In addition, architecture using CO2 refrigerant shows interesting performances regardless of location and despite degraded regimes during heat peaks. However, the maintenance score can be a limiting factor for installing more energy efficient systems. Two other scenarios are studied: with photovoltaic panels; with financial support. Photovoltaic panels help improving cost and environmental performances, but also strongly depend on maintenance performances. Financial support helps facilities using low-global-warming-potential refrigerant to be more competitive than those using high-global-warming-potential refrigerant.

Integrated Design of a Supermarket Refrigeration System by Means of Experimental Design Adapted to Computational Problems

In this paper, an integrated design of a supermarket refrigeration system has been used to obtain a process with better operability. It is formulated as a multi-objective optimization problem where control performance is evaluated by six indices and the design variables are the number and discrete power of each compressor to be installed. The functional dependence between design and performance is unknown, and therefore the optimal configuration must be obtained through a computational experimentation. This work has a double objective: to adapt the surface response methodology (SRM) to optimize problems without experimental variability as are the computational ones and show the advantage of considering the integrated design. In the SRM framework, the problem is stated as a mixture design with constraints and a synergistic cubic model where a D-optimal design is applied to perform the experiments. Finally, the multi-objective problem is reduced to a single objective one by means of a desirability function. The optimal configuration of the power distribution of the three compressors, in percentage, is (50,20,20). This solution has an excellent behaviour with respect to the six indices proposed, with a significant reduction in time oscillations of controlled variables and power consumption compared with other possible power distributions.